Tag Archives: Complexity

Apple buying Beats might be a safe-to-fail experiment

The music industry is a complex adaptive system (CAS). The industry is full of autonomous agents who have good and bad relationships with each other. Behaviours and reactive consequences can build on each other.  Media writers and industry analysts are also agents who are  easily attracted to big events. Their comments and opinions add to the pile and fuel momentum. However the momentum is nonlinear. Interest in the  topic will eventually fall off  as pundits tire and move on or a feverish pitch continues. Alternatively a CAS phenomenon called tipping point occurs. The music industry then changes. It might be small or a huge paradigm shift. It can’t be predicted; it will just emerge . In complexity jargon, the the system doesn’t evolve but co-evolves.  It’s asymmetrical – in other words, there is no reset or UNDO button to go back prior to the event.

While I might have an opinion about Apple buying Beats, I’m more interested in observing music industry behaviour. Here’s one perspective. I’ll use complexity language and apply the Cynefin Framework.

1. Apple is applying Abductive thinking and playing a hunch.

“Let’s buy Beats because the deal might open up some cool serendipitous opportunities. We can also generate some free publicity and let others promote us, and have fun keeping people guessing.  Yeh, it may be a downer if they write we’re nuts. But on the upside they are helping us by driving the competition crazy.”

2. Apple is probing the music industry by conducting a safe-to-fail experiment.

“It’s only $3.2B so we can use some loose change in our pockets. Beats is pulling in $1B annual revenue so really it’s no big big risk.”

3. Apple will monitor agent behaviour and observe what emerges.

“Let’s see what the media guys say.
“Let’s read about researchers guessing what we’re doing.”
“Let’s watch the business analysts  tear their hair out trying to figure out a business case  with a positive NPV. Hah! If they only knew a business case is folly in the Complex domain since predictability is impossible. That’s why we’re playing a hunch which may or may not be another game changer for us.”

4. If the Apple/Beats deal starts going sour, dampen or shut down the experiment.

“Let’s have our people on alert to detect unintended negative consequences. We can dampen the impact by introducing new information and watch the response. If we feel it’s not worth saving, we’ll cut our losses. The benefits gained will be what we learn from the experiment.”

5. If the Apple/Beats deal takes off, accelerate and search for new behaviour patterns to exploit.

“The key agents in the CAS to watch are the consumers. Observing what they buy is easy.  What’s more important is monitoring what they don’t buy.  We want to discover where they are heading and what the is strange attractor. It might be how consumers like to stream music, how they like to listen to music (why only ears?), or simply cool headphones are fashion statements.”

6. Build product/service solutions that  exploit this new pattern opportunity.

“Once we discover and understand the new consumer want, be prepared to move quickly.  Let’s ensure our iTunes Radio people are in the loop as well as the AppleTV and iWatch gangs. Marketing should be ready to use the Freemium business model. We’ll offer the new music  service for free to create barriers of entry to block competitors  who can’t afford to play the new game. It will be similar to our free medical/safety alert service we’ll offer with the iWatch. Free for Basic and then hook ’em with the gotta-have Premium.”

7. Move from the Complex domain to the Complicated Domain to establish order and stability.

“As soon as we’re pretty certain our Betas are viable, we’ll put our engineering  and marketing teams on it to release Version 1. We’ll also start thinking about Version 2. As before, we’ll dispense with ineffective external consumer focus groups. We’ll give every employee the product/service and gather narrative (i.e., stories) about their experiences. After all, employees are consumers and if it’s not great for us, then it won’t be great for the public.

Besides learning from ourselves, let’s use our Human Sensor network to cast  a wide net on emerging new technologies and ideas. Who knows, we might find another Beats out there we can buy to get Version 2 earlier to market.”

Fantasy? Fiction? The outcomes may be guesses but the Probe, Sense, Respond process in the Cynefin Complex Domain isn’t.

 

The Case against the Business Case

Business cases are developed typically for big projects that require a huge commitment of resources (time, people, money). Calculations are based on best-guess revenue forecasts and cost estimates. It is written from a “fail-safe” perspective – think of everything that could go wrong, devise mitigating action plans, and cover off uncertainties as assumptions. Not only is the task challenging and energy sucking, you never really know if you’ve missed something because “what you don’t know is what you don’t know.” So, you “time-box” the effort and proclaim “Oh well, good enough”.

In 2010, Dan Gardner in this book Future Babble took a critical look at expert predictions and the psychology that explains why people believe them even though they consistently fail.

“Seminal research by UC Berkeley professor Philip Tetlock proved that the average expert is no more accurate than a flipped coin.”

Gardner based his book on current research in cognitive psychology, political science, and behavioural economics. These are intangibles that a business case cannot dollarize and frequently end up being subjectively treated in a risk assessment section.

With respect to the Cynefin Framework, the Business Case tool resides in the Complicated Domain and works well in an ordered, linear, predictable environment. It will probably continue as the approval mechanism for cause & effect solutions. Sense, Analyze, and Respond.

Just be aware that the Business Case has very little value when dealing with a Complex Domain issue where uncertainty rules, predictions are fallible, and unknown unknowns abound. Here, we must Probe, Sense, and Respond by conducting “safe-to-fail” experiments.

Why Managers Haven’t Embraced Complexity

This is the title of an article written by Richard Straub in the Harvard Business Review HR Blog. The notion of applying Complexity science to management has been around for over 20 years. So why hasn’t it caught on? Why are managers and leaders reluctant to see the world as it is: non-linear, turbulent, ambiguous, unpredictable, and uncertain? Straub offers 3 reasons:

  1. Managers don’t want to give up control. 
    Today’s dominating business paradigm is Systems Thinking and the control of information. Before that it was Scientific Management and the control of processes. Imagine the resistance put up by those not willing to give up Taylorism and accept emerging ideas like socio-technical systems, learning organizations, etc. Now systems thinkers who once fought an uphill battle to introduce their ideas are being asked to give up their control of information and don’t resist/deny/block but embrace emerging ideas like complexity, networks, cognition. Reluctant managers will eventually change because they will discover that their old methods can’t resolve today’s problems. “Keep at it, try harder” no longer works and becomes a waste of time.
  2. Technology isn’t powerful enough.
    In engineering school I was taught “When in doubt, make a model”. I later realized that students in business and economics were also told the same thing. So we learned early that models were useful to proxy the real world. We didn’t have powerful computers (only slide rules) to perform detailed calculations; therefore, we learned from experienced craftsmen and professionals the “rules of thumb” they successfully deployed. Fast forward to today and consider the computer horsepower we have to create mathematical models to handle real world complexity. The internet, big data analytics, cloud computing, supercomputers et al are rapidly changing the IT landscape. We now know how human sensor networks can turn stories told by humans into data points that can be analyzed and support better decision-making.
  3. The prospect of non-human decision-making is too unnerving.
    If we had infinite computer processing power, would we be able to create a precise model of a complex system such as Health Care? Aviation? Public education? Electric power industry? Physicist Murray Gell-man says no: “The only valid model of a complex system is the system itself.”
    Machines are designed to perform “work-as-imagined.” Because human designers can’t imagine everything, machines are limited in what they can do. Humans are the best agents in a complex system to deal with unknown unknowns, unknowables, and the unimaginable.

Straub makes the point there has been a gradual change in mindset, pushed along by the increasingly evident damage of narrow, simplistic thinking. Here we are 10+ years into the 21st century and note the number of industrial age ideas still being widely used. The public education system continues run on a factory model. Health care remains using a craft model.

The movement from Safety-I to Safety-II hasn’t happened as quickly as we had hoped. In the latter case, perhaps by embracing complexity and applying ideas like the Cynefin framework and narrative inquiry, we will be able to accelerate the operationalizing of Safety-II.

Click here to read the Richard Straub article.

Thinking about Paradigms and Paradigm Shifts

I was initially introduced to the notion of paradigms and paradigm shift by Joel Barker. For me, he was able to take a science phenomenon into the world of business.

From Wikipedia: “The word [paradigm] has come to refer very often now to a thought pattern in any scientific discipline or other epistemological context.” …Since the 1960s, the term [paradigm shift} has also been used in numerous non-scientific contexts to describe a profound change in a fundamental model or perception of events, even though Kuhn himself restricted the use of the term to the hard sciences.”
I can relate to non-scientific contexts. As a FranklinCovey trainer, I introduce the concept of paradigms very early in a 7 Habits of Highly Effective People workshop. 7 Habits is all about changing human behaviour and it starts with the paradigms, the beliefs, the mindsets, we possess. In many cases, the paradigms that people hold dearly are not wrong or incorrect; they are insufficient. In addition, if you become highly skilled at using a hammer, you see every problem as a nail.

Insufficiency

I hold a Professional Engineer license. I enjoy analyzing problems, finding cause & effect relations, optimizing choices, and implementing solutions. Life is good. When I can make all the decisions, life is really good. However, when other people get involved (especially stakeholders who are not engineers) I get extremely frustrated. I also like to work in a very linear, sequential fashion. I dislike uncertainities, unknowns, unpredictable behaviours. What’s wrong with people? How can they disagree with me? Why can’t they see it my way? As a budding engineer, this was my attitude. Thankfully I quickly matured and discovered I had tunnel vision. I could only view things from my vantage point. The world was much broader and wider than that. In Cynefin framework terms, my early formative career years clearly put me in the Complicated Domain. In many instances I was able to argue that I was right. However, I was insufficient because I did not recognize the Unordered side where Complexity and Chaos resided. I had read some things about complexity thinking but still didn’t have a complete picture. That changed when I read Dave’s and Mary’s 2007 HBR article Leader’s Framework for Decision Making.

Too Good for your own Good

Whenever I took a course or attended a workshop, I discovered my return to my office was often filled with employee trepidation. “Uh oh! What has Gary learned now that he wants to try out on us?” In later years as a consultant, I would come equipped with tried and proven methods, tools, and templates. Yesterday’s posting about wanting to start an engagement with traditional interviewing is an example. Hey! Why not? It’s worked in the past and therefore, should work just as well again. As experts we need to ensure that we are using the right tools at the right time for the right reasons.
In Cynefin framework terms, it’s perfectly okay to recommend Simple Domain solutions such as Training 101 when a lack of basic skills is the problem. Here we’re dealing with known knowns. We must be aware, however, when we propose resolving a Complex Domain issue using a Complicated Domain approach. It’s that ability to use a hammer well inside us which wants to immediately jump in and start analyzing instead of patiently stepping back and probing the system. It’s getting the client to appreciate that a safety culture problem won’t go away if more rules are written, training is mandated for all, and documenting crew inspections is added to the supervisor’s already overloaded checklist.

I once was asked in a 7 Habits workshop must a perspective change be earth shattering, tsunami-sized to be called a paradigm shift? My opinion was no. Humour, for instance, is a paradigm shift. Standup comedians like Bob Hope, Bill Crosby, Jerry Seinfeld knew how the play the brain to create laughter. Question: What is a paradigm worth? Answer: 20 cents If you aren’t smiling (or groaning), don’t feel bad. It’s just an indication of the patterns that have formed in your brain. I will be exploring how the brain works in a future posting. Plus provide an explanation if you didn’t get the joke.
I’d like to end today’s ramblings with story of a paradigm shift in my own home.

We were at the dinner table with my young daughter, Jennifer, sitting across from me. “Daddy! I can count to 10!’ she proudly exclaimed. “Great, Jen! Show me!” “Okay. 1,2,3,4,5,6,7,8,9,10. See! I did it!” “Good job! Way to go!”
Now being the father who enjoyed giving his kids a challenge, I then asked: “Now, can you count backwards?”
“Sure!” she smiled.
Jen proceeded to jump out of the chair, turn her back to me and confidently shouted: “1,2,3,4,5,6,7,8,9,10. See! I did it!”.
My wife and I hit the floor laughing. Yes, it was a .001 paradigm shift on the Richter scale but one that we will always remember fondly.